resnext50_64x4d

paddle.vision.models. resnext50_64x4d ( pretrained=False, **kwargs ) [source]

ResNeXt-50 64x4d model from “Aggregated Residual Transformations for Deep Neural Networks”

Parameters

pretrained (bool, optional) – If True, returns a model pre-trained on ImageNet. Default: False.

Examples

import paddle
from paddle.vision.models import resnext50_64x4d

# build model
model = resnext50_64x4d()

# build model and load imagenet pretrained weight
# model = resnext50_64x4d(pretrained=True)

x = paddle.rand([1, 3, 224, 224])
out = model(x)

print(out.shape)
# [1, 1000]